The economical units in the world face great and rapid challenges in all aspects, a matter that requires facing these challenges throughout continuous improving and developing in their performance to keep their competitive position "place".

       The Benchmarking Technique is one of the modern managerial tools that are proved to be successful in application throughout making continuous comparisons between products or services and the best – performance levels the compete with it . This is achieved to develop its performance and give it the competitive criterion with which it faces its competitors.

Abstract

This research attempt to explain the essential aspects of one important model in management of Bank risks , that is (stress testing) , which increase the concentrate on it resulting the negative affects of Global financial crisis that it accuar in 2008 to study the application possibilities in iraqian banks to enhancing the safety and financial soundness Becuase the classical tools  in Risk management don’t give clear image on Banks ability  in facing risks, hence the Basel committee on Banking supervision focusing in agreement of Basel 2,3 on stress testing when it doing the internal capital adequacy assessment process (ICAAP) .

To achieving the reseach obje

Polish Academy of Sciences

Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th

Nutrient enrichment of Sawa lake water was made using different nitrogen and phosphorus concentrations during autumn and spring at three stations. Different concentrations of nitrogen, phosphorus and N: P ratios were used to test variations in phytoplankton population dynamics. Nitrogen at a concentration of 25 µmole.l-1 and N: P ratio of 10:1 gave highest phytoplankton cell number at all stations and seasons. A total of 64 algal taxa dominated by Bacillariophyceae followed by Cyanophyceae and Chlorophyceae were identified. The values of Shannon index of diversity were more than one in the studied stations.

Abstract

                 The study aims to clarify the impact of the adoption of the International Financial Reporting Standard (IFRS16) on lease contracts in the General Iraqi Insurance Company on the financial statements, and thus the impact on financial ratios and indicators, Since the financial reporting standard considers lease contracts as an asset called the right to use the asset and is offset by a liability, this changes the way the financial statements are presented, with an addition to both the asset and liability sides. In order to show the extent to which the adoption of the standard reflects on the financial performance

Abstract

The present paper attempts to detect the level of (COVID-19) pandemic panic attacks among university students, according to gender and stage variables.

To achieve this objective, the present paper adopts the scale set up by (Fathallah et al., 2021), which has been applied electronically to a previous cross-cultural sample consisting of (2285) participants from Arab countries, including Iraq. The scale includes, in its final form, (69) optional items distributed on (6) dimensions:  physical symptoms (13) items, psychological and emotional symptoms (12) items, cognitive and mental symptoms (11) items, social symptoms (8) items, general symptoms (13) items and daily living practices (12) items

This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.